1. Field of Invention
The present invention relates generally to an improved data processing system and in particular to a database model. Still more particularly, the present invention relates to a computer implemented method and computer usable program code to generate, organize, manipulate and analyze data in a relational database for managing and improving equipment long-term supportability.
2. Background Description
A commodity frequently has multiple parts. Each of these parts may require repair, replacement, and/or redesign during various phases of the commodity's useable life cycle. As used herein, a commodity includes, but is not limited to, any type of equipment or machine, such as an airplane, car, boat, truck, van, construction vehicle, forklift, computer hardware, radar equipment, engine, transmission, or any other equipment having one or more repairable parts.
To improve commodity operation and supportability, as well as to identify commodity part improvement candidates, a user may need to compare the costs of maintenance, repair, and replacement of all the commodity parts and related subparts. To determine which part in a commodity is driving costs, a user needs to identify parts that are responsible for the greatest share of repair and maintenance costs. In other words, the user needs to identify parts that are driving the commodity's maintenance and repair costs. These parts are referred to as cost driver parts.
A user can manually identify cost driver parts for a given commodity by comparing the cost of repair and maintenance of the subparts. A user may then attempt to manually determine whether continued repair of a given cost driver part is more cost effective than replacement or redesign of the part or subparts. A user may make this determination by comparing the costs of repairing with the costs for replacing the part with an identical part, replacing the part with an alternative part, or redesign of the part or replacement parts. This comparison of the various costs associated with the cost driver part allows a user to determine which option is the most cost effective and/or will yield the best return on investment (ROI).
To make a return on investment determination, however, a user must identify cost driver parts. Typically, a user will identify cost driver parts based on the greatest current costs for repair and/or replacement of the parts. The user then makes a manual search through all part history cost data and part maintenance and repair records to obtain past and current cost data associated with the cost driver parts. The user obtains and compares current part costs for repair and replacement where the cost driver part is used within the commodity. The user also obtains and compares part reuse in different functional areas of the commodity, costs for alternate parts, and costs associated with any previous part configurations, such as historical part redesigns.
This process is both difficult and time consuming for users because the user is required to sort through voluminous part information and data sources in an attempt to manually locate relevant information of interest. If a user cannot locate all the desired part cost information, the user may be unable to manually calculate the past and current costs for repairing and replacing the given part. If a user cannot calculate accurate past and current costs, the user may be unable to make a meaningful determination as to whether continued repair, redesign, or replacement of the part may be most cost effective. This process may also be inaccurate or misleading when a user has incomplete part cost data, or incorrectly calculates past or current costs associated with maintenance, repair, and replacement of the part.
In addition, this process only provides the user with information regarding a single part. If the user wishes to obtain data regarding costs for repair and replacement for another part-related to the cost driver part or a subpart, the user must repeat the time consuming and arduous process of manually searching available data sources for part cost data relating to the new part or subpart, and manually calculate the past and current cost for repair, replacement, or redesign of the parts and subparts.
Finally, this process only permits a user to obtain cost information for past and current repairs and replacement costs. This process does not provide any information regarding future cost projections for maintenance, repair, and replacement of parts and subparts. Thus, a user is frequently unable to make an accurate determination as to whether a repair, replacement, or redesign of a given cost driver part or subpart will provide the best future return on investment.
Therefore, it would be advantageous to have an improved computer implemented method and computer usable program code to provide a commodity part database to organize and present commodity part data to a user for managing and improving commodity supportability over a commodity's projected life cycle.